Analyse et conception d'algorithmes et d'architectures embarqués à bord de satellites d'observation spatiale : application au satellite GAIA et généralisation à la compression d'images astronomiques
Bibliographic record
Abstract
Avec l'augmentation de la resolution des instruments embarques dans les satellites d'observation spatiale et leur mise sur orbites de plus en plus lointaines (ce qui reduit leur debit d'emission vers la Terre), il est devenu necessaire, de deporter a bord certains traitements. Or les methodes classiques de compression d'image sont a la fois trop couteuses et inadaptees a des images de ciel etoile. Il est par contre nettement plus efficace de detecter le fond puis l'eliminer en n'envoyant que le signal. Dans ce cadre, nous avons propose des solutions algorithmiques et architecturales depuis la selection des pixels des objets a envoyer jusqu'a leur stockage dans l'attente de leur emission. En particulier, nous avons propose de nouveaux algorithmes de selection, ajoute une phase de precompression et concu une architecture de stockage faible consommation pour un tampon de telemetrie a grande capacite. La faisabilite de ces solutions a ete demontree pour le satellite GAIA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".